Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
Strahlentherapie und Onkologie
Published in: Strahlentherapie und Onkologie 10/2020

Open Access 01-10-2020 | Magnetic Resonance Imaging | Review Article

Radiomics for liver tumours

Authors: Constantin Dreher, MD, Philipp Linde, MD, PD Dr. Judit Boda-Heggemann, MD, PhD, PD Dr. med. Bettina Baessler, MD

Published in: Strahlentherapie und Onkologie | Issue 10/2020

Login to get access

Abstract

Current research, especially in oncology, increasingly focuses on the integration of quantitative, multiparametric and functional imaging data. In this fast-growing field of research, radiomics may allow for a more sophisticated analysis of imaging data, far beyond the qualitative evaluation of visible tissue changes. Through use of quantitative imaging data, more tailored and tumour-specific diagnostic work-up and individualized treatment concepts may be applied for oncologic patients in the future. This is of special importance in cross-sectional disciplines such as radiology and radiation oncology, with already high and still further increasing use of imaging data in daily clinical practice. Liver targets are generally treated with stereotactic body radiotherapy (SBRT), allowing for local dose escalation while preserving surrounding normal tissue. With the introduction of online target surveillance with implanted markers, 3D-ultrasound on conventional linacs and hybrid magnetic resonance imaging (MRI)-linear accelerators, individualized adaptive radiotherapy is heading towards realization. The use of big data such as radiomics and the integration of artificial intelligence techniques have the potential to further improve image-based treatment planning and structured follow-up, with outcome/toxicity prediction and immediate detection of (oligo)progression. The scope of current research in this innovative field is to identify and critically discuss possible application forms of radiomics, which is why this review tries to summarize current knowledge about interdisciplinary integration of radiomics in oncologic patients, with a focus on investigations of radiotherapy in patients with liver cancer or oligometastases including multiparametric, quantitative data into (radio)-oncologic workflow from disease diagnosis, treatment planning, delivery and patient follow-up.

Literature
  1. Lambin P et al (2012) Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer 48(4):441–446PubMedPubMed CentralView Article
  2. Bickelhaupt S et al (2017) Prediction of malignancy by a radiomic signature from contrast agent-free diffusion MRI in suspicious breast lesions found on screening mammography. J Magn Reson Imaging 46(2):604–616PubMedView Article
  3. Rosenstein BS et al (2014) Radiogenomics: radiobiology enters the era of big data and team science. Int J Radiat Oncol Biol Phys 89(4):709–713PubMedPubMed CentralView Article
  4. Cunliffe A et al (2015) Lung texture in serial thoracic computed tomography scans: correlation of radiomics-based features with radiation therapy dose and radiation pneumonitis development. Int J Radiat Oncol Biol Phys 91(5):1048–1056PubMedPubMed CentralView Article
  5. Perrin T et al (2018) Short-term reproducibility of radiomic features in liver parenchyma and liver malignancies on contrast-enhanced CT imaging. Abdom Radiol 43(12):3271–3278View Article
  6. Bickelhaupt S et al (2018) Radiomics based on adapted diffusion Kurtosis imaging helps to clarify most mammographic findings suspicious for cancer. Radiology 287(3):761–770PubMedView Article
  7. Li ZC et al (2018) Multiregional radiomics profiling from multiparametric MRI: Identifying an imaging predictor of IDH1 mutation status in glioblastoma. Cancer Med 7(12):5999–6009PubMedPubMed CentralView Article
  8. Andrea C‑G et al (2020) Developments in predictive biomarkers for hepatocellular carcinoma therapy. Expert Rev Anticancer Ther 20(1):63–74View Article
  9. Lewis S et al (2019) Volumetric quantitative histogram analysis using diffusion-weighted magnetic resonance imaging to differentiate HCC from other primary liver cancers. Abdom Radiol 44(3):912–922View Article
  10. Wu J et al (2019) Radiomics-based classification of hepatocellular carcinoma and hepatic haemangioma on precontrast magnetic resonance images. BMC Med Imaging 19(1):23PubMedPubMed CentralView Article
  11. Oyama A et al (2019) Hepatic tumor classification using texture and topology analysis of non-contrast-enhanced three-dimensional T1-weighted MR images with a radiomics approach. Sci Rep 9(1):8764PubMedPubMed CentralView Article
  12. Wu M et al (2019) Predicting the grade of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature. Eur Radiol 29(6):2802–2811PubMedView Article
  13. Guo D et al (2019) Radiomics analysis enables recurrence prediction for hepatocellular carcinoma after liver transplantation. Eur J Radiol 117:33–40PubMedView Article
  14. Gerum S et al (2018) Stereotactic body radiation therapy (SBRT) in patients with hepatocellular carcinoma and oligometastatic liver disease. Radiat Oncol 13(1):100PubMedPubMed CentralView Article
  15. Mahadevan A et al (2018) Stereotactic Body Radiotherapy (SBRT) for liver metastasis—clinical outcomes from the international multi-institutional RSSearch(R) Patient Registry. Radiat Oncol 13(1):26PubMedPubMed CentralView Article
  16. Nabavizadeh N et al (2018) Safety and efficacy of accelerated hypofractionation and stereotactic body radiation therapy for hepatocellular carcinoma patients with varying degrees of hepatic impairment. Int J Radiat Oncol Biol Phys 100(3):577–585PubMedView Article
  17. Andratschke N et al (2018) The SBRT database initiative of the German Society for Radiation Oncology (DEGRO): patterns of care and outcome analysis of stereotactic body radiotherapy (SBRT) for liver oligometastases in 474 patients with 623 metastases. BMC Cancer 18(1):283PubMedPubMed CentralView Article
  18. Wahl DR et al (2016) Outcomes after stereotactic body radiotherapy or radiofrequency ablation for hepatocellular carcinoma. J Clin Oncol 34(5):452–459PubMedView Article
  19. Klein J et al (2015) Prospective longitudinal assessment of quality of life for liver cancer patients treated with stereotactic body radiation therapy. Int J Radiat Oncol Biol Phys 93(1):16–25PubMedView Article
  20. Ost P et al (2018) Surveillance or metastasis-directed therapy for oligometastatic prostate cancer recurrence: a prospective, randomized, multicenter phase II trial. J Clin Oncol 36(5):446–453PubMedView Article
  21. Palma DA et al (2019) Stereotactic ablative radiotherapy versus standard of care palliative treatment in patients with oligometastatic cancers (SABR-COMET): a randomised, phase 2, open-label trial. Lancet 393(10185):2051–2058PubMedView Article
  22. Gomez DR et al (2019) Local consolidative therapy vs. maintenance therapy or observation for patients with oligometastatic non-small-cell lung cancer: long-term results of a multi-institutional, phase II, randomized study. J Clin Oncol 37(18):1558–1565PubMedPubMed CentralView Article
  23. Deutsch E et al (2019) Optimising efficacy and reducing toxicity of anticancer radioimmunotherapy. Lancet Oncol 20(8):e452–e463PubMedView Article
  24. Dupre A et al (2017) Curative-intent treatment of recurrent colorectal liver metastases: a comparison between ablation and resection. Eur J Surg Oncol 43(10):1901–1907PubMedView Article
  25. Klement RJ et al (2019) The impact of local control on overall survival after stereotactic body radiotherapy for liver and lung metastases from colorectal cancer: a combined analysis of 388 patients with 500 metastases. BMC Cancer 19(1):173PubMedPubMed CentralView Article
  26. Van Cutsem E et al (2006) Towards a pan-European consensus on the treatment of patients with colorectal liver metastases. Eur J Cancer 42(14):2212–2221PubMedView Article
  27. Rusthoven KE et al (2009) Multi-institutional phase I/II trial of stereotactic body radiation therapy for liver metastases. J Clin Oncol 27(10):1572–1578PubMedView Article
  28. Riemsma RP et al (2013) Transarterial (chemo)embolisation versus no intervention or placebo intervention for liver metastases. Cochrane Database Syst Rev Cd009498:4
  29. Cirocchi R et al (2012) Radiofrequency ablation in the treatment of liver metastases from colorectal cancer. Cochrane Database Syst Rev Cd006317:6
  30. Levy J et al (2018) Intra-arterial therapies for unresectable and chemorefractory colorectal cancer liver metastases: a systematic review and meta-analysis. HPB 20(10):905–915PubMedView Article
  31. Franzese C et al (2018) Liver metastases from colorectal cancer: propensity score-based comparison of stereotactic body radiation therapy vs. microwave ablation. J Cancer Res Clin Oncol 144(9):1777–1783PubMedView Article
  32. Petrelli F et al (2018) Stereotactic body radiotherapy for colorectal cancer liver metastases: a systematic review. Radiother Oncol 129(3):427–434PubMedView Article
  33. Takeda A et al (2016) Phase 2 study of stereotactic body radiotherapy and optional transarterial chemoembolization for solitary hepatocellular carcinoma not amenable to resection and radiofrequency ablation. Cancer 122(13):2041–2049PubMedView Article
  34. Durand-Labrunie J et al (2020) Curative irradiation treatment of hepatocellular carcinoma: a multicenter phase 2 trial. Int J Radiat Oncol Biol Phys 3016(19):34512–34512
  35. Lo CH et al (2017) Survival and prognostic factors for patients with advanced hepatocellular carcinoma after stereotactic ablative radiotherapy. PLoS ONE 12(e0177793):5
  36. Shen P‑C et al (2019) Comparison of stereotactic body radiation therapy and transarterial chemoembolization for unresectable medium-sized hepatocellular carcinoma. Int J Radiat Oncol Biol Phys 105(2):307–318PubMedView Article
  37. Comito TLM, Franzese C, Clerici E, Pedicini V, Poretti D, Solbiati L, Rimassa L, Scorsetti M (2020) PB02-02 SBRT vs TAE/TACE in Hepatocellular carcinoma: results from a Phase III trial (NTC02323360). European Association for the Study of the Liver (EASL), Prague
  38. Brunner TB et al (2019) Stereotactic body radiotherapy dose and its impact on local control and overall survival of patients for locally advanced intrahepatic and extrahepatic cholangiocarcinoma. Radiother Oncol 132:42–47PubMedView Article
  39. Rajyaguru DJ et al (2018) Radiofrequency ablation versus stereotactic body radiotherapy for localized hepatocellular carcinoma in nonsurgically managed patients: analysis of the national cancer database. J Clin Oncol 36(6):600–608View ArticlePubMed
  40. Honda Y et al (2013) Stereotactic body radiation therapy combined with transcatheter arterial chemoembolization for small hepatocellular carcinoma. J Gastroenterol Hepatol 28(3):530–536PubMedView Article
  41. Jacob R et al (2015) Adjuvant stereotactic body radiotherapy following transarterial chemoembolization in patients with non-resectable hepatocellular carcinoma tumours of 〉/= 3 cm. HPB 17(2):140–149PubMedView Article
  42. Michalopoulos GK (2010) Liver regeneration after partial hepatectomy: critical analysis of mechanistic dilemmas. Am J Pathol 176(1):2–13PubMedPubMed CentralView Article
  43. Dawson LA, Ten Haken RK (2005) Partial volume tolerance of the liver to radiation. Semin Radiat Oncol 15(4):279–283PubMedView Article
  44. Jung J et al (2013) Radiation-induced liver disease after stereotactic body radiotherapy for small hepatocellular carcinoma: clinical and dose-volumetric parameters. Radiat Oncol 8:249PubMedPubMed CentralView Article
  45. Cheng JC et al (2002) Radiation-induced liver disease after three-dimensional conformal radiotherapy for patients with hepatocellular carcinoma: dosimetric analysis and implication. Int J Radiat Oncol Biol Phys 54(1):156–162PubMedView Article
  46. Su TS, Luo R, Liang P, Cheng T, Zhou Y, Huang Y (2018) A prospective cohort study of hepatic toxicity after stereotactic body radiation therapy for hepatocellular carcinoma. Radiother Oncol 129(1):136–142. https://​doi.​org/​10.​1016/​j.​radonc.​2018.​02.​031View ArticlePubMed
  47. Gkika E et al (2018) The role of albumin-bilirubin grade and inflammation-based index in patients with hepatocellular carcinoma treated with stereotactic body radiotherapy. Strahlenther Onkol 194(5):403–413PubMedView Article
  48. Ito K et al (2019) Whole-liver radiotherapy for diffuse liver metastases improves liver enzymes and related factors. Acta Oncol 58(4):512–514PubMedView Article
  49. Miften M, Vinogradskiy Y, Moiseenko V, et al (2018) Radiation Dose-Volume Effects for Liver SBRT [published online ahead of print, 2018 Jan 6]. Int J Radiat Oncol Biol Phys S0360–3016(17)34527–34523. https://​doi.​org/​10.​1016/​j.​ijrobp.​2017.​12.​290View Article
  50. McPartlin A et al (2017) Long-term outcomes of phase 1 and 2 studies of SBRT for hepatic colorectal metastases. Int J Radiat Oncol Biol Phys 99(2):388–395PubMedView Article
  51. Hiwatashi K et al (2016) The evaluation of liver function and surgical influence by ICGR15 after chemotherapy for colorectal liver metastases. J Cancer 7(5):595–599PubMedPubMed CentralView Article
  52. Huffman BM et al (2018) Hepatotoxicity after immune checkpoint inhibitor therapy in melanoma: natural progression and management. Am J Clin Oncol 41(8):760–765View ArticlePubMed
  53. Dreher C et al (2016) Metabolic liver function after stereotactic body radiation therapy for hepatocellular carcinoma. Acta Oncol 55(7):886–891PubMedView Article
  54. Toesca DAS et al (2017) Assessment of hepatic function decline after stereotactic body radiation therapy for primary liver cancer. Pract Radiat Oncol 7(3):173–182PubMedView Article
  55. DeLeve LD, Shulman HM, McDonald GB (2002) Toxic injury to hepatic sinusoids: sinusoidal obstruction syndrome (veno-occlusive disease). Semin Liver Dis 22(1):27–42PubMedView Article
  56. Osmundson EC et al (2015) Predictors of toxicity associated with stereotactic body radiation therapy to the central hepatobiliary tract. Int J Radiat Oncol Biol Phys 91(5):986–994PubMedView Article
  57. Toesca DA et al (2017) Central liver toxicity after SBRT: an expanded analysis and predictive nomogram. Radiother Oncol 122(1):130–136PubMedView Article
  58. Koay EJ, Owen D, Das P (2018) Radiation-induced liver disease and modern radiotherapy. Semin Radiat Oncol 28(4):321–331PubMedPubMed CentralView Article
  59. Hanna GG et al (2018) UK consensus on normal tissue dose constraints for stereotactic radiotherapy. Clin Oncol 30(1):5–14View Article
  60. Pan CC et al (2010) Radiation-associated liver injury. Int J Radiat Oncol Biol Phys 76(3 Suppl):S94–100PubMedPubMed CentralView Article
  61. Grimm J et al (2011) Dose tolerance limits and dose volume histogram evaluation for stereotactic body radiotherapy. J Appl Clin Med Phys 12(2):3368View ArticlePubMed
  62. Méndez Romero A, de Man RA (2016) Stereotactic body radiation therapy for primary and metastatic liver tumors: from technological evolution to improved patient care. Best Pract Res Clin Gastroenterol 30(4):603–616PubMedView Article
  63. Asbell SO et al (2016) Introduction and clinical overview of the DVH risk map. Semin Radiat Oncol 26(2):89–96PubMedView Article
  64. Ma S, Xie H, Wang H, et al (2019) MRI-Based Radiomics Signature for the Preoperative Prediction of Extracapsular Extension of Prostate Cancer. J Magn Reson Imaging 50(6):1914–1925. https://​doi.​org/​10.​1002/​jmri.​26777View ArticlePubMed
  65. Li M et al (2016) Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma. Oncotarget 7(11):13248–13259PubMedPubMed CentralView Article
  66. Shan Q‑Y et al (2019) CT-based peritumoral radiomics signatures to predict early recurrence in hepatocellular carcinoma after curative tumor resection or ablation. Cancer Imaging 19(1):11–11PubMedPubMed CentralView Article
  67. Zhou Y et al (2017) CT-based radiomics signature: a potential biomarker for preoperative prediction of early recurrence in hepatocellular carcinoma. Abdom Radiol 42(6):1695–1704View Article
  68. Xu X et al (2019) Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma. J Hepatol 70(6):1133–1144PubMedView Article
  69. Bakr S et al (2017) Noninvasive radiomics signature based on quantitative analysis of computed tomography images as a surrogate for microvascular invasion in hepatocellular carcinoma: a pilot study. J Med Imaging 4(4):41303–41303View Article
  70. Peng J et al (2018) A radiomics nomogram for preoperatively predicting prognosis of patients in hepatocellular carcinoma. Transl Cancer Res 7(4):936–946View Article
  71. Chen S et al (2019) Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging. Eur Radiol 29(8):4177–4187PubMedView Article
  72. Veres DS et al (2019) Radiomic detection of microscopic tumorous lesions in small animal liver SPECT imaging. EJNMMI Res 9(1):67PubMedPubMed CentralView Article
  73. Houweling AC et al (2013) FDG-PET and diffusion-weighted MRI in head-and-neck cancer patients: implications for dose painting. Radiother Oncol 106(2):250–254PubMedView Article
  74. Prezzi D et al (2018) The impact of MRI sequence on tumour staging and gross tumour volume delineation in squamous cell carcinoma of the anal canal. Eur Radiol 28(4):1512–1519PubMedView Article
  75. Fode MM et al (2017) A phase I study on stereotactic body radiotherapy of liver metastases based on functional treatment planning using positron emission tomography with 2‑[(18)F]fluoro-2-deoxy-d-galactose. Acta Oncol 56(11):1614–1620PubMedView Article
  76. Thian YL, Riddell AM, Koh DM (2013) Liver-specific agents for contrast-enhanced MRI: role in oncological imaging. Cancer Imaging 13(4):567–579PubMedPubMed CentralView Article
  77. Joo I et al (2016) Monitoring vascular disrupting therapy in a rabbit liver tumor model: relationship between tumor perfusion parameters at IVIM diffusion-weighted MR imaging and those at dynamic contrast-enhanced MR imaging. Radiology 278(1):104–113PubMedView Article
  78. Woo S et al (2014) Intravoxel incoherent motion diffusion-weighted MR imaging of hepatocellular carcinoma: correlation with enhancement degree and histologic grade. Radiology 270(3):758–767PubMedView Article
  79. Bickelhaupt S et al (2018) Radiomics based on adapted diffusion Kurtosis imaging helps to clarify most mammographic findings suspicious for cancer. Radiology 287(3):761–770PubMedView Article
  80. Sun K et al (2015) Breast cancer: diffusion Kurtosis MR imaging—diagnostic accuracy and correlation with clinical-pathologic factors. Radiology 277(1):46–55PubMedView Article
  81. d’Assignies G et al (2013) High sensitivity of diffusion-weighted MR imaging for the detection of liver metastases from neuroendocrine tumors: comparison with T2-weighted and dynamic gadolinium-enhanced MR imaging. Radiology 268(2):390–399PubMedView Article
  82. Surov A, Meyer HJ, Wienke A (2017) Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis. Oncotarget 8(35):59492–59499PubMedPubMed CentralView Article
  83. Jensen JH et al (2005) Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med 53(6):1432–1440PubMedView Article
  84. Le Bihan D et al (1988) Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 168(2):497–505PubMedView Article
  85. Dalah E et al (2014) Variability of target and normal structure delineation using multimodality imaging for radiation therapy of pancreatic cancer. Int J Radiat Oncol Biol Phys 89(3):633–640PubMedView Article
  86. Liu Y et al (2019) MRI-based treatment planning for liver stereotactic body radiotherapy: validation of a deep learning-based synthetic CT generation method. BJR 92(1100):20190067–20190067PubMedView ArticlePubMed Central
  87. Deng Z, Guo Q, Zhu Z (2019) Dynamic regulation of level set parameters using 3D Convolutional neural network for liver tumor segmentation. J Healthc Eng p:4321645
  88. Vivanti R et al (2018) Patient-specific and global convolutional neural networks for robust automatic liver tumor delineation in follow-up CT studies. Med Biol Eng Comput 56(9):1699–1713PubMedView Article
  89. Vorontsov E et al (2017) Metastatic liver tumour segmentation with a neural network-guided 3D deformable model. Med Biol Eng Comput 55(1):127–139PubMedView Article
  90. Fu Y et al (2018) A novel MRI segmentation method using CNN-based correction network for MRI-guided adaptive radiotherapy. Med Phys 45(11):5129–5137PubMedView Article
  91. Zhang Y et al (2018) A knowledge-based approach to automated planning for hepatocellular carcinoma. J Appl Clin Med Phys 19(1):50–59PubMedView Article
  92. Velec M et al (2017) Validation of biomechanical deformable image registration in the abdomen, thorax, and pelvis in a commercial radiotherapy treatment planning system. Med Phys 44(7):3407–3417PubMedView Article
  93. Witt JS, Rosenberg SA, Bassetti MF (2020) MRI-guided adaptive radiotherapy for liver tumours: visualising the future. Lancet Oncol 21(2):e74–e82PubMedView Article
  94. Dogan N et al (2019) EP-2023 Predictive value of delta-radiomics features extracted from MR Images in image-guided liver SBRT. Radiother Oncol 133:S1109–S1110View Article
  95. Bentzen SM et al (2010) Quantitative analyses of normal tissue effects in the clinic (QUANTEC): an introduction to the scientific issues. Int J Radiat Oncol Biol Phys 76(3 Suppl):S3–S9PubMedPubMed CentralView Article
  96. El Naqa I et al (2017) Radiogenomics and radiotherapy response modeling. Phys Med Biol 62(16):R179–R206PubMedPubMed CentralView Article
  97. Cunliffe A et al (2015) Lung texture in serial thoracic computed tomography scans: correlation of radiomics-based features with radiation therapy dose and radiation pneumonitis development. Int J Radiat Oncol Biol Phys 91(5):1048–1056PubMedPubMed CentralView Article
  98. Scalco E et al (2013) Texture analysis for the assessment of structural changes in parotid glands induced by radiotherapy. Radiother Oncol 109(3):384–387PubMedView Article
  99. Cai W et al (2019) A radiomics-based nomogram for the preoperative prediction of posthepatectomy liver failure in patients with hepatocellular carcinoma. Surg Oncol 28:78–85PubMedView Article
  100. Ibragimov B et al (2018) Development of deep neural network for individualized hepatobiliary toxicity prediction after liver SBRT. Med Phys 45(10):4763–4774PubMedView Article
  101. Park HJ et al (2019) Radiomics analysis of gadoxetic acid-enhanced MRI for staging liver fibrosis. Radiology 290(2):380–387PubMedView Article
  102. Ding Y et al (2015) Assessing liver function in patients with HBV-related HCC: a comparison of T(1) mapping on Gd-EOB-DTPA-enhanced MR imaging with DWI. Eur Radiol 25(5):1392–1398PubMedView Article
  103. Katsube T et al (2011) Estimation of liver function using T1 mapping on Gd-EOB-DTPA-enhanced magnetic resonance imaging. Invest Radiol 46(4):277–283PubMedView Article
  104. Toesca DAS et al (2018) Strategies for prediction and mitigation of radiation-induced liver toxicity. J Radiat Res 59(suppl_1):i40–i49PubMedPubMed CentralView Article
  105. Reimer RP, Reimer P, Mahnken AH (2018) Assessment of therapy response to transarterial radioembolization for liver metastases by means of post-treatment MRI-based texture analysis. Cardiovasc Intervent Radiol 41(10):1545–1556PubMedView Article
  106. Cozzi L et al (2017) Radiomics based analysis to predict local control and survival in hepatocellular carcinoma patients treated with volumetric modulated arc therapy. BMC Cancer 17(1):829PubMedPubMed CentralView Article
  107. Kim J et al (2018) Predicting survival using pretreatment CT for patients with hepatocellular carcinoma treated with transarterial chemoembolization: comparison of models using radiomics. Ajr Am J Roentgenol 211(5):1026–1034PubMedView Article
  108. Mokrane F‑Z et al (2020) Radiomics machine-learning signature for diagnosis of hepatocellular carcinoma in cirrhotic patients with indeterminate liver nodules. Eur Radiol 30(1):558–570PubMedView Article
  109. Zhao L et al (2019) Prediction for early recurrence of intrahepatic mass-forming cholangiocarcinoma: quantitative magnetic resonance imaging combined with prognostic immunohistochemical markers. Cancer Imaging 19(1):49–49PubMedPubMed CentralView Article
  110. Ohara K et al (1997) Radiation tolerance of cirrhotic livers in relation to the preserved functional capacity: analysis of patients with hepatocellular carcinoma treated by focused proton beam radiotherapy. Int J Radiat Oncol Biol Phys 38(2):367–372PubMedView Article
  111. Mastrocostas K et al (2019) Imaging post-stereotactic body radiation therapy responses for hepatocellular carcinoma: typical imaging patterns and pitfalls. Abdom Radiol 44(5):1795–1807View Article
  112. Boda-Heggemann J et al (2016) MRI morphologic alterations after liver SBRT: direct dose correlation with intermodal matching. Strahlenther Onkol 192(9):641–648PubMedView Article
  113. Boda-Heggemann J et al (2018) Direct dose correlation of MRI morphologic alterations of healthy liver tissue after robotic liver SBRT. Strahlenther Onkol 194(5):414–424PubMedView Article
  114. Sanuki N et al (2014) Threshold doses for focal liver reaction after stereotactic ablative body radiation therapy for small hepatocellular carcinoma depend on liver function: evaluation on magnetic resonance imaging with Gd-EOB-DTPA. Int J Radiat Oncol Biol Phys 88(2):306–311PubMedView Article
  115. Sampath S, Rahmanuddin S, Sahoo P, et al (2019) Change in Apparent Diffusion Coefficient Is Associated With Local Failure After Stereotactic Body Radiation Therapy for Non-Small Cell Lung Cancer: A Prospective Clinical Trial. Int J Radiat Oncol Biol Phys 105(3):659–663. https://​doi.​org/​10.​1016/​j.​ijrobp.​2019.​06.​2536View ArticlePubMed
  116. Zwanenburg A, Leger S, Vallières M, Löck S (2016) Image biomarker standardisation initiative. (arXiv:1612.07003 [cs.CV])
  117. Zhovannik I et al (2019) Learning from scanners: Bias reduction and feature correction in radiomics. Clinical and Translational Radiation Oncology 19:33–38PubMedPubMed CentralView Article
  118. Zhao B et al (2016) Reproducibility of radiomics for deciphering tumor phenotype with imaging. Sci Rep 6:23428–23428PubMedPubMed CentralView Article
  119. Zhao B et al (2014) Exploring variability in CT characterization of tumors: a preliminary phantom study. Transl Oncol 7(1):88–93PubMedPubMed CentralView Article
  120. Traverso A et al (2018) Repeatability and Reproducibility of Radiomic Features: A Systematic Review. Int J Radiat Oncol Biol Phys 102(4):1143–1158PubMedPubMed CentralView Article
  121. Shafiq-Ul-Hassan M et al (2017) Intrinsic dependencies of CT radiomic features on voxel size and number of gray levels. Med Phys 44(3):1050–1062PubMedView Article
  122. Baessler B, Weiss K, Pinto Dos DS (2019) Robustness and reproducibility of radiomics in magnetic resonance imaging: a phantom study. Invest Radiol 54(4):221–228PubMedView Article
  123. Um H et al (2019) Impact of image preprocessing on the scanner dependence of multi-parametric MRI radiomic features and covariate shift in multi-institutional glioblastoma datasets. Phys Med Biol 64(16):165011–165011PubMedView Article
Metadata
Title
Radiomics for liver tumours
Authors
Constantin Dreher, MD
Philipp Linde, MD
PD Dr. Judit Boda-Heggemann, MD, PhD
PD Dr. med. Bettina Baessler, MD
Publication date
01-10-2020
Publisher
Springer Berlin Heidelberg
Published in
Strahlentherapie und Onkologie / Issue 10/2020
Print ISSN: 0179-7158
Electronic ISSN: 1439-099X
DOI
https://doi.org/10.1007/s00066-020-01615-x

Other articles of this Issue 10/2020

Strahlentherapie und Onkologie 10/2020 Go to the issue

Literatur kommentiert

Die Herzmortalität nach Strahlentherapie, Chemotherapie und endokriner Therapie des Mammakarzinoms

Original Article

Magnetic resonance imaging-based radiomic features for extrapolating infiltration levels of immune cells in lower-grade gliomas

Literatur kommentiert

Unterschiede in der Lebensqualität über 5 Jahre nach Therapie des lokal begrenzten Prostatakarzinoms mit verschiedenen Behandlungsoptionen

Review Article

Applications of radiomics and machine learning for radiotherapy of malignant brain tumors

Review Article

The role of radiomics in prostate cancer radiotherapy

Literatur kommentiert

Vielversprechende Langzeitergebnisse zum Einsatz von Anastrozol zur Prävention von Brustkrebs bei postmenopausalen Hochrisikopatientinnen